Method for controlling a robot device

A robot device including a control device including a processor, the control device configured to control the robot device, the control device configured to:

• acquire an image of an environment of the robot device, the environment being a working range of a robot arm of the robot device;
• process the image using a neural network, the neural network being configured to output from the image for at least one action parameter value, a respective value image with pixel values for multiple pixels, the pixel value for each pixel of the multiple pixels indicating an evaluation of an action that is specified by the action parameter value and the position of the pixel in the value image, and the neural network being configured to ascertain an evaluation of each action from an intermediate evaluation of the action and an evaluation of a state of the environment of the robot device, wherein the neural network has an encoder network and a decoder network with a bottleneck between the encoder network and the decoder network and skip connections between the encoder network and the decoder network;
• select, from multiple actions that characterize a skill of the robot device in each case, a particular action from among the multiple actions for which the pixel value of the pixel in the value image is at a maximum for the action parameter value at the position that specifies the action together with the action parameter value;
• and
• control the robot device to carry out the selected action.

A computer-readable medium on which is stored commands for controlling a robot device, the commands, when executed by a processor, causing the processor to perform the following steps:

• acquiring an image of an environment of the robot device, the environment being a working range of a robot arm of the robot device;
• processing the image using a neural network, the neural network being configured to output from the image for at least one action parameter value, a respective value image with pixel values for multiple pixels, the pixel value for each pixel of the multiple pixels indicating an evaluation of an action that is specified by the action parameter value and the position of the pixel in the value image, and the neural network being configured to ascertain an evaluation of each action from an intermediate evaluation of the action and an evaluation of a state of the environment of the robot device, wherein the neural network has an encoder network and a decoder network with a bottleneck between the encoder network and the decoder network and skip connections between the encoder network and the decoder network;
• selecting, from multiple actions that characterize a skill of the robot device in each case, a particular action from among the multiple actions for which the pixel value of the pixel in the value image is at a maximum for the action parameter value at the position that specifies the action together with the action parameter value;
• and
• controlling the robot device to carry out the selected action.